Next Article in Journal
A First Attempt to Combine NIRS and Plenoptic Cameras for the Assessment of Grasslands Functional Diversity and Species Composition
Previous Article in Journal
Recovery of Orange Peel Essential Oil from ‘Sai-Namphaung’ Tangerine Fruit Drop Biomass and Its Potential Use as Citrus Fruit Postharvest Diseases Control
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Research on the Effect of Conservation Tillage Mode on the Suppression of Near-Surface Dust in Farmland

1
College of Engineering, China Agricultural University, Beijing 100083, China
2
Key Laboratory of Agricultural Equipment for Conservation Tillage, Ministry of Agricultural and Rural Affairs, Beijing 100083, China
3
Beijing Municipal Bureau of Agriculture and Rural Affairs, Beijing 100029, China
4
Institution of Mechanical and Electrical Engineering, Beijing Vocational College of Agriculture, Beijing 100085, China
*
Author to whom correspondence should be addressed.
Submission received: 8 April 2022 / Revised: 7 May 2022 / Accepted: 10 May 2022 / Published: 17 May 2022

Abstract

:
In order to explore the beneficial effects of conservation tillage (straw burial, stubble + straw mulching, straw mulching) compared with traditional tillage on suppressing farmland dust and the law on farmland wind erosion, PM2.5 and PM10, in this study, according to the distribution characteristics of farmland dust particles “from large to small” and “from bottom to top”, the self-designed dust collector and farmland dust online monitoring system were used to analyze the amount of wind and dust, PM2.5 and PM10, near the surface of farmland. A comparative study on the dust emission of farmland from conservation tillage and traditional tillage is conducted in two dimensions. The mobile wind tunnels are used to simulate and verify the release of PM2.5 and PM10 near the surface of farmland. Among them, the monitoring of farmland wind erosion shows that compared with traditional farming, the wind erosion of straw burial, stubble + straw mulching, and straw mulching decreased by 29.37%, 40.73%, and 36.61%, respectively, and 90~250 μm large-size sand particles are reduced by 37.2%, 74.7%, and 31.6%, respectively. The monitoring results of PM2.5 and PM10 near the surface of the farmland showed that the stubble + straw mulching model is compared with the traditional farming farmland. The reductions were 42.5% and 40.8%, significantly higher than the straw burial and straw mulching modes. The multiple linear regression analysis of the monitoring data showed that the PM2.5 and PM10 release concentrations near the surface of farmland had the highest correlation with wind speed, followed by soil moisture and temperature. Wind tunnel test verification shows that the following three protective tillage modes: straw burial, straw mulching, and stubble + straw mulching, have apparent inhibitory effects on PM2.5 and PM10 released on farmland compared with traditional tillage modes. In 1~8 m/s interval, the release concentration of PM2.5 in the modes of straw burial, stubble + straw mulching, and straw mulching decreased by 15.34~41.17%, 32.05~48.56%, and 28.85~42.40%, and the PM10 release concentration decreased by 19.44~36.47%, 35.90~52.00%, and 25.83~50.63%, respectively, which are consistent with the monitoring results of PM2.5 and PM10 near the surface of farmland. The research results show that the beneficial effects of each model on farmland dust suppression are stubble + straw mulching > straw mulching > straw burial. The study is intended to provide theoretical support for promoting conservation tillage and the return of high-quality straw mulch to the field in Beijing.

1. Introduction

The wind erosion of farmland soil is one of the critical factors that cause desertification and affect air quality in arid and semi-arid regions of northern China. The tiny particles produced by soil wind erosion have a very significant impact on the concentrations of PM2.5 and PM10 in the atmosphere [1,2,3].
Farmland dust is farmland soil wind erosion, which refers to the atmospheric particulate matter of a specific size range formed by the displacement of loose particles on the surface under the action of a specific wind force and entering the ambient air. These particles are suspended in the atmosphere, causing the atmosphere in the area and surrounding areas to suffer from pollution; in general, the smaller the particle size, the greater the harm to the human body [4,5].
The source analysis results of much atmospheric particulate matter show that, besides human factors, soil wind erosion dust diffused from the surface into the atmosphere is an essential factor affecting the ambient air quality. Under the action of severe wind erosion of farmland, the fine particles (clay and organic matter) rich in nutrients on the soil surface will be significantly lost, resulting in the loss of nutrients in the soil, soil coarsening, soil carbon loss, land productivity decline, and more severe problems. Land desertification, sandstorms, and wind erosion of farmland soil seriously affect regional economic development and the quality of people’s living environment [6,7,8,9].
Therefore, it is of great significance to study the monitoring of seasonal exposed farmland dust to protect the environment and cultivated land. It is mainly affected by surface straw coverage, wind speed, and soil humidity. Experts at home and abroad have performed a series of studies on farmland dust monitoring, mainly focusing on the spatial and temporal distribution and variation characteristics of dust emissions, using research methods such as analysis, simulation, estimation, source analysis, etc., to explore farming methods, environmental changes, soil types, land surface, and the influence of factors such as coverage degree on farmland dust release. In terms of the contribution of soil wind erosion to the concentration of atmospheric particulates, Lin conducted a study on farmland dust emissions from the time dimension [10]. The results showed that bare farmland had the most significant impact on ambient air quality in spring and verified it using the CMB source analysis model. In terms of measurement models, atmospheric diffusion models are currently used to estimate the emission levels of particulate pollutants in the atmosphere in areas with insufficient monitoring conditions. Pan used multiple linear regression (REC) and fitting analysis to evaluate air quality [11]. Using the CAMS model, Sara Karamiet et al. studied the dominant weather model of dust storms in the Persian Gulf [12]. Sun studied the spatial pattern of the dust emission process of farmland soil wind erosion under various modes, determined the impact of dust emission, and formulated effective protection measures [13]. In addition, many scholars have also carried out research on the relationship between soil dust release and meteorological factors and soil factors. Cavatina in Mexico found that PM10 released in farmland was negatively correlated with relative humidity in the air [14], and Aimar in Argentina also showed that soil The release of wind-eroded PM10 is negatively correlated with soil moisture [15]. Zhao used a wind tunnel to study the relationship between soil moisture content and farmland soil wind erosion and found that soil moisture content is a critical factor in inhibiting wind erosion [16].
At present, reasonably and effectively controlling the source of PM2.5 and PM10 releases and exploring the inhibitory effect of surface crop coverage on farmland dust has become the focus of research. Based on backward trajectory analysis, Zhu found that the frequency of PM10 transported to Beijing in spring was the highest in southern Mongolia, western Inner Mongolia, and the Loess Plateau [17]. Liu showed that straw mulching on the ground combined with stubble retention could consolidate the soil and reduce water evaporation [18]. Cong discussed the role of stubble and straw mulching in reducing farmland soil wind erosion in western Liaoning’s aeolian sandy semi-arid area [19]. Wasson, R.J. et al. theoretically deduced an exponential relationship between vegetation cover and farmland dust emission [20]. Catherine bresaola et al. tested in the dune area along the Atlantic coast. They proved that the density, height, and width of surface cover significantly impact soil wind erosion [21].
Dry fields are widely distributed in the Beijing area. In spring and autumn, the farmland soil is bare or semi-bare. Compared with conservation tillage, the topsoil of traditional tillage is finely broken. When the wind is strong in spring and winter, the finely broken soil particles on the surface are easily blown away by the strong wind, resulting in serious farmland soil dust. It has a significant impact on the air quality of Beijing and surrounding areas. Conservation tillage technology is an important means to restrain wind erosion of farmland soil. Through less tillage or no-tillage measures, the disturbance of the tillage components to the soil can be reduced. At the same time, the return of crop straws to the field can keep the surface of the farmland covered with straw residues, increase the surface roughness, and weaken the surface wind speed.
The research mainly focuses on modeling the farmland dust emission process, combining theory and mathematical models to analyze the relevant factors of farmland dust emission, or carrying out specific research on a particular factor affecting farmland dust emission. The research on farmland dust is not systematic and comprehensive. This research has carried out multi-dimensional and systematic research on farmland dust particles “from large to small” and “from bottom to top”. The concentrations of PM2.5 and PM10 near the surface of farmland are comprehensively analyzed through wind tunnel test verification. It is planned to clarify the influence laws of straw burial, stubble + straw mulching, and straw mulching modes on farmland dust suppression. This study can provide theoretical support for promoting conservation tillage according to local conditions in the high-incidence area of farmland dust in northern Beijing, suppress farmland dust, and promote high-quality straw mulching and returning to the field.

2. Determination Method

2.1. Test Site and Comparison Mode Selection

In order to monitor the effects of three types of conservation tillage techniques, including straw burial, stubble + straw mulching, and straw mulching, in suppressing the seasonally exposed farmland dust. As shown in Figure 1, between September 2020 and October 2021, the monitoring team built nine farmland dust monitoring points based on local crop planting and straw treatment characteristics in Miyun, Huairou, and Yanqing.
The straw burial mode is that the straw crusher crushes the corn straw, the surface soil is mixed with the straw by the rotary cultivator, and the mixed burial depth is about 15 cm. The mode of stubble + straw mulching is to crush and cover the ground after corn harvest, and the stubble height is about 20 cm. The straw mulching mode is to use the straw returning to the machine to crush the surface straw after corn harvest so that the straw residue covers the surface without tillage. The straw coverage rate is between 40% and 60%. The traditional tillage modes are the plow-plow and rotary tiller. After the mechanical operation, the surface soil is finely crushed and not covered with straw.
The experimental area is located in the north of Beijing, between 40°13′ and 41°40′ N, 115°44′ and 117°30′ E, with an annual average temperature between 8 and 13°. The climate intersects temperate continental monsoon climate and warm temperate semi-humid continental monsoon climate. Due to the low temperature and high wind speed in winter in Miyun, Huairou, and Yanqing, dust is easily generated in farmland exposure. Therefore, the monitoring team established straw burial and traditional comparison modes in Henan Zhai town, Fengjiayu town, and Gubeikou town in Miyun District. stubble + straw mulching and traditional farming comparison modes in Qiaozi town, Yangsong town, and Changshaoying town in Huairou District. Jiuxian town, Shenjiaying town, and Jingzhuang town in Yanqing District established a comparison model between straw mulching and traditional farming and further clarified the critical role of different conservation tillage in restraining farmland dust compared with traditional tillage by using technical means such as farmland wind erosion collection, near-surface PM2.5, and PM10 monitoring, wind tunnel test and measurement.

2.2. Farmland Wind Erosion Monitoring

In order to measure the distribution of wind erosion, a dust collector is installed at the monitoring point. The China Institute for Conservation Tillage independently developed the dust collector comprises a sand mining device, tail spoiler, support bracket, fixed bolt, and support frame [22], as shown in Figure 2. Among them, the sand collector is the central part of the dust collector. The tailwind deflector is used to automatically adjust the direction of the air inlet so that the sand outlet can always face the wind direction and ensure the effective collection of farmland dust. The fixed bolts fix the sand mining device at different heights of the support rod. The distances between the sand mining ports of the five sand mining devices of the sand dust collector are 10 cm, 25 cm, 60 cm, 100 cm, and 150 cm from the surface, respectively, and they can collect sand at five heights. As shown in Figure 3, during the working process of the dust collector, the airflow, surface sand, and a small amount of straw enter the air inlet of the sand mining device, and the airflow leaves the sand mining device through the 60-mesh screen. In contrast, sand and straw remain in the mining device. The stratification of sand and straw is completed in the sander and by the internal filter screen. Dust monitors the amount of wind erosion and the particle size distribution of sand and dust at different heights. In order to obtain the change in farmland wind erosion in different periods, the sand and dust samples collected by the sand-dust collector at the monitoring point were regularly sampled. The sand and dust in the sand collector at different heights were collected and bagged, respectively, to calculate the amount of sand carried by a unit area.
The amount of wind erosion is the amount of sand transported per unit area. The specific calculation formula is as follows (1). Due to the small total weight of sand and dust, to reduce the measurement error, a high-precision balance with an accuracy of 0.0001 g is used for weighing in this monitoring report.
Wind   erosion   amount g / cm 2 = Dust   weight   per   unit   time ( g ) Sand   inlet   area   ( cm 2 )
In order to obtain the particle size distribution of sand dust at each height, 25 mesh, 65 mesh, 80 mesh, 180 mesh, and 700 mesh screens were used to screen and classify the collected sand and dust samples. And ≥710 μm, 250~710 μm, 180~250 μm, 90~180 μm, 20~90 μm, and <20 μm obtained. There are six grades in total, and the weight of each grade is weighed separately to obtain the distribution percentage of sand dust particle size of each grade.

2.3. Near-Surface PM2.5 and PM10 Monitoring

Farmland soil dust is an essential source of PM2.5 and PM10. Wind-eroded fugitive dust on exposed farmland surface soil affects PM2.5 and PM10 concentrations and air quality in the atmosphere through diffusion and other processes [23]. At the same time, factors such as wind speed, surface temperature, humidity, and rainfall will have a specific impact on PM2.5 and PM10 concentrations in the near-surface air of farmland [24].
The monitoring team used the farmland dust online monitoring system independently developed by the China Institute for Conservation Tillage to measure the concentration changes of PM2.5 and PM10 near the surface of the farmland [25]. Figure 4 and Figure 5 show that the monitoring system comprises the central controller, PM2.5 and PM10 measurement sensor, wind speed sensor, soil temperature, and humidity sensor, rain gauge, battery, solar panel, and other hardware. A solar panel and battery power the monitoring system. The sensor uploads the collected information to the central controller through the RS485 protocol and then uploads it to the cloud platform through the MQTT communication protocol. Finally, the real-time display of monitoring information is completed at the mobile or PC terminal. The monitoring system can complete the collection of near-surface air quality, wind speed, wind direction, 0~5 cm soil temperature and humidity, rainfall, accumulated dust, and other indicators. The sampling frequency is adjustable, and the maximum sampling frequency is once per minute.
The monitoring team mainly carried out observation and analysis of changes in the concentrations of PM2.5 and PM10 in the air within 120 cm of the surface. Sampling height is set at 90 cm near the surface, and monitoring system is installed in the open area around the center of the farmland. The system calculates the concentrations of PM2.5 and PM10 in the air from the mass of PM2.5 and PM10 and the volume of sampled air. It analyzes the relevant factors affecting the concentrations of PM2.5 and PM10 near the surface according to the measured indexes.

2.4. Wind Tunnel Test Simulation Verification

In order to measure the PM2.5 and PM10 emissions from farmland under different farming modes and surface wind speeds, clarify the influence of different wind speeds and farming modes on PM2.5 and PM10 releases from near-surface farmland, and simulate and verify the reliability of near-surface soil dust monitoring, the PM2.5 and PM10 emissions of farmland soil are studied through field wind tunnel tests [26,27]. The movable wind tunnel used in this study is mainly composed of a variable frequency fan, acrylic sealing plate, frame, air intake section, transition section, test section, and collection segment, as shown in Figure 6.
The fan provides the air source for the entire wind tunnel; the transition section is the transition between the circular section of the power section and the rectangular section of the stable section. The airflow is gradually kept uniform and stable in the transition section. The airflow reaches the test section evenly accelerated; the test section is the core of the wind tunnel. The length × width × height is 0.9 m × 0.45 m × 0.45 m, respectively. The bottom of the wind tunnel in the test section is the field surface, and in the test carried out in this section, PM2.5 and PM10 emission measurements are completed at the collection end.
Before the start of the test, two laser inhalable dust continuous measuring instruments were installed in the collection section of the wind tunnel to measure the PM2.5 and PM10 concentrations at different surface wind speeds at 10 cm and 20 cm heights, respectively. In order to obtain the PM2.5 and PM10 emissions of farmland under different surface wind speed conditions, the speed of the fan in the power section is adjusted by the frequency converter. The wind speed in the wind tunnel of the test section is 1 m/s, 2 m/s, 4 m/s, 6 m/s, and 8 m/s. During the test, the dust continuous measuring instrument automatically records the concentration values of PM2.5 and PM10 once every 1 min. The continuous blowing time of each test is 10 min. Each test is repeated three times to take the average value. The installation of surface treatment and dust measuring instruments in the test section is shown in Figure 7 and Figure 8.

3. Results and Analysis

3.1. Measurement and Analysis of Wind Erosion in Farmland

According to the dust characteristics of farmland dust in different monitoring areas and the local agronomic planting requirements, the monitoring team selected different conservation tillage modes in different monitoring areas to explore the inhibition law of three conservation tillage modes of straw burial, stubble + straw mulching, and straw mulching on farmland large particle dust under the comparison between different conservation tillage modes and traditional tillage modes.

3.1.1. Measurement of Farmland Wind Erosion

From October 2020 to December 2020, the monitoring team took three samples from farmland dust collectors in Miyun District, Huairou District, and Yanqing District, with a sampling interval of about 15 days, and measured and counted farmland wind erosion and particle size distribution at each monitoring point through the above measurement methods, as shown in Table 1.
As shown in Table 1, the wind erosion monitoring results show that the farmland dust in Miyun District, Huairou District, and Yanqing District of Beijing is mainly distributed in the sand collector at 10 cm and 25 cm. With the increase in the sampling height of the sand collector, the collected wind erosion is significantly reduced. Therefore, the blown sand particles in the farmland within the height range of 0~25 cm have a considerable weight. It shows that the airflow in farmland is insufficient to transport large particles of aeolian sand dust to a higher atmospheric level.
As shown in Table 2, conservation tillage can significantly reduce surface wind erosion compared with traditional tillage. The test results of three monitoring areas show that the erosion of straw burial in Miyun District is reduced by 29.37%, the erosion of stubble + straw mulching in the Huairou district is reduced by 40.73% compared with traditional tillage, and the erosion of straw mulching in Yanqing District is reduced by 36.61%. The wind erosion of the land collected by the three conservation tillage modes shows that applying the conservation tillage mode to cover the surface with straw can effectively reduce surface wind erosion. Among them, high-quality conservation tillage (stubble + straw mulching) has a more noticeable effect on the suppression of farmland dust. The beneficial effects of farmland dust suppression are stubble + straw mulching > straw mulching > straw burial. Therefore, for the high-risk area of farmland dust in northern Beijing, adopting high-quality conservation tillage suitable for local agronomic planting requirements according to local conditions can effectively reduce the amount of farmland surface wind erosion.

3.1.2. Particle Size Analysis of Wind Erosion in Farmland

The particle size distribution of sand dust at each height of the monitoring points in Miyun District, Huairou District, and Yanqing District. Under the treatment of conservation tillage and traditional tillage, the particle size distribution of conservation tillage sand dust and traditional tillage sand dust is obtained, as shown in Figure 9, Figure 10, Figure 11, Figure 12, Figure 13 and Figure 14.
The experimental results of the particle size distribution of fugitive dust in conservation tillage and traditional tillage farmland show that the particle size distribution of dust is different in any mode. The particle size of farmland dust in traditional tillage and conservation tillage modes is mainly concentrated between 20 and 90 μm. With the increase in sampling height, the average diameter of dust particles decreases significantly. The closer the surface, the larger the particle size of fugitive dust collected is. The main reason is that the particles with large particle sizes have high gravity, and the buoyancy generated by airflow is challenging to bring them to high places.
The proportion of small and medium-sized sand dust in conservation tillage is relatively high. Mainly related to straw covering the surface, increasing the surface roughness, and slowing down the wind speed near the farmland surface so that large particles of sand cannot be blown up. Compared with the corresponding traditional tillage, the three conservation tillage modes of straw burial, stubble + straw covering, and straw covering significantly reduce the sand particles above 90 μm. It shows that the conservation tillage mode can effectively reduce the number of large sand particles blown up to the ground. The sand particles below 90 μm are also reduced to a certain extent. For atmospheric pollution, in the comparison of the three conservation tillage modes with traditional tillage, the large-size sand particles of 90~250 μm were significantly reduced, among which straw burial reduced the large-size sand particles by 37.2%, stubble + straw mulching reduced the large-size sand particles by 74.7%, and straw mulching reduced the large-size sand particles by 31.6%. Therefore, the protective tillage mode of high-quality stubble and straw mulching has the most apparent effect on the transition inhibition of large particles on the farmland surface.

3.2. Farmland Near-Surface PM2.5 and PM10 Monitoring

From October to December 2021, the monitoring data of PM2.5 and PM10 at the monitoring points in Miyun District, Huairou District, and Yanqing District of Beijing were statistically analyzed. One sample was taken every five adjacent days during this period, and nine online samples were taken. Calculate the average value of the sampling results to obtain the corresponding index value and conduct a statistical analysis of the data. Finally, the curves of near-surface PM2.5 and PM10 concentrations with wind speed, soil temperature, humidity, and rainfall under traditional tillage mode and conservation tillage mode are obtained in Figure 15, Figure 16, Figure 17, Figure 18, Figure 19 and Figure 20.
During this period, the daily average concentrations of PM2.5 and PM10 at 90 cm near the surface of the farmland were 28.77 μg/m3 and 35.69 μg/m3, respectively. The variation range was 14.09 μg/m3~48.03 μg/m3, 21.36~54.37 μg/m3, and the average daily concentrations of PM2.5 and PM10 near the surface of the farmland under the straw burying model were 23.81 μg/m3 and 26.56 μg/m3. The variation range was 12.09~45.17 μg/m3, 12.98~51.37 μg/m3. Compared with traditional tillage, the near-surface PM2.5 and PM10 of conservation tillage farmland decreased by 17.2% and 25.6%, respectively.
The average daily concentrations of PM2.5 and PM10 near the surface of the traditional farmland in the Huairou District were 39.71 μg/m3 and 52.15 μg/m3, respectively, and the variation ranges were 26.02~66.03 μg/m3 and 36.6~86.68 μg/m3. The average daily concentrations of PM2.5 and PM10 near the surface of the stubble + straw mulching conservation tillage farmland were 22.85 μg/m3 and 30.89 μg/m3, and the variation ranges were 7.76~47.41 μg/m3 and 10.64~66.39 μg/m3. Compared with traditional tillage, the near-surface PM2.5 and PM10 of cultivated farmland decreased by 42.5% and 40.8%, respectively.
The average daily concentrations of PM2.5 and PM10 near the surface of the traditional farmland in the Huairou District were 35.57 μg/m3 and 46.29 μg/m3, respectively, and the variation ranges were 11.48~62.98 μg/m3 and 14.81~76.53 μg/m3. The average daily concentrations of PM2.5 and PM10 near the surface of the straw mulched farmland were 22.43 μg/m3 and 32.9 μg/m3, and the variation ranges were 5.22~32.48 μg/m3 and 7.86~54.81 μg/m3. Compared with traditional tillage, the PM2.5 and PM10 near the surface of the conservation tillage farmland decreased by 36.9% and 28.9%, respectively.
The above analysis results show that the protective tillage mode of Huairou stubble + straw mulch reduces 42.5% and 40.8% of PM2.5 and PM10 near the surface of the traditional farmland and is significantly higher than the Yanqing straw mulching and Miyun straw burial modes. Inhibition of dust in farmland: stubble + straw mulching > straw mulching > straw burial.
Using Minitab software, a multiple linear regression analysis was performed on all regional monitoring data from October to December, with PM10 and PM2.5 as independent variables, along with temperature, humidity, wind speed, and rainfall. The regression analysis results are shown in Table 3.
As can be seen from the analysis of the variance table of PM10, the test model is exceptionally significant (p < 0.01). Among the main factors, temperature, humidity, and wind speed are incredibly significant, while the influence of rainfall is not significant. Through the analysis of variance, the regression equation between each factor and PM10 concentration is obtained, as shown in Equation (2) as follows:
ln ( PM 10 ) = 4.936 + 0.1146 temperature 0.0694 humidity 0.873 wind   speed + 0.300 rainfall
As can be seen from the analysis of the variance table of PM2.5, the test model is exceptionally significant (p < 0.01). Among the main factors, temperature, humidity, and wind speed are incredibly significant, while the influence of rainfall is not significant. Through the analysis of variance, the regression equation between each factor and PM2.5 concentration is obtained, as shown in Equation (3) as follows:
ln ( PM 2.5 ) = 4.534 + 0.1159 temperature 0.0612 humidity 0.867 wind   speed + 0.308 rainfall

3.3. Wind Tunnel Test Simulation Verification

3.3.1. Wind Tunnel Test Simulation Analysis

During the period from October 2021 to December 2021, the monitoring team in Miyun District, Huairou District, and Yanqing District of Beijing focused on different farming modes (straw burial, stubble + straw mulching, straw mulching), and farmland PM2.5 and PM10 release concentrations were tested and analyzed under different wind speeds. The test results are shown in Figure 21, Figure 22, Figure 23 and Figure 24.
The release concentration values of PM2.5 and PM10 collected at 10 cm near the surface are lower than 20 cm, indicating that the tiny particles blown by the wind tunnel will be suspended near the surface, increasing the concentration of small particles at a certain height from the surface. In addition, the wind tunnel test results also show that compared with the traditional tillage model, the conservation tillage model has a noticeable inhibitory effect on the near-surface PM2.5 and PM10 concentration release of farmland.
Among them, in straw burial compared with the traditional tillage mode in Miyun District, the release concentrations of PM2.5 and PM10 at the sampling height of 10 cm decreased by 27.15% and 29.18%, respectively. PM2.5 and PM10 at the sampling height of 20 cm decreased by 28.80% and 31.15%, respectively.
Stubble + straw mulching compared with the traditional tillage mode in Huairou District, the release concentrations of PM2.5 and PM10 at the sampling height of 10 cm decreased by 34.54% and 39.02%, respectively, and the release concentrations of PM2.5 and PM10 at the sampling height of 20 cm decreased by 43.17% and 46.85% respectively.
Straw mulching compared with the traditional tillage mode in Yanqing District, the release concentrations of PM2.5 and PM10 at the sampling height of 10 cm decreased by 33.09% and 40.91%, respectively, and the release concentrations of PM2.5 and PM10 at the sampling height of 20 cm decreased by 34.50% and 36.61%, respectively.
Compared with the three conservation tillage modes of straw burial, stubble + straw mulching, and straw mulching, the inhibition effects of PM2.5 and PM10 released near the surface of farmland are as follows: stubble + straw mulching > straw mulching > straw burial. Among them, the high-quality protective model of stubble + straw mulching monitored in Huairou District has the most apparent inhibition on the release of PM2.5 and PM10 near the surface of farmland, which is consistent with the above monitoring results of PM2.5 and PM10 near the surface of farmland.
As shown in Figure 25, Figure 26, Figure 27 and Figure 28, the test results show that the concentration of PM2.5 and PM10 released from farmland increases significantly with the increase in the surface wind speed. Under the conditions of different sampling heights and wind speeds, the comparison results between the three conservation tillage modes and the traditional tillage modes show that the higher the surface wind speed, the more pronounced the protective tillage mode on farmland PM2.5 and PM10 release inhibition effect. When the surface wind speed is 1 m/s, straw burial, straw mulching, and stubble + straw mulching PM2.5 release. The average concentrations decreased by 15.34%, 28.85%, and 32.05%, and the released concentrations of PM10 decreased by 19.44%, 25.83%, and 35.90% on average. When the surface wind speed reaches 8 m/s, the PM2.5 release concentrations of straw burial, straw mulching, and stubble + straw mulching are reduced by 41.17%, 42.40%, and 48.56% on average, and the PM10 release concentrations by 36.47%, 50.63%, and 52.00%.

3.3.2. Analyses of Variance of Different Tillage Mode

According to the analysis in Table 4, the p-value of farming methods and wind tunnel wind speed is less than 0.001, with extremely significant differences in the release of PM2.5 and PM10 near the farmland surface under different farming methods and wind tunnel wind speed. Similarly, the interaction terms between farming methods and wind tunnel wind speed are more excellent than 0.05, so there is no significant difference between the two interaction terms. Therefore, the analysis of variance shows that the release of PM2.5 and PM10 near the farmland surface can be influenced by changing farming methods and farmland surface wind speed. The significant analysis results of different tillage methods are shown in Table 5. The multiple comparisons of the Duncan method show significant differences between stubble + strain mulching and straw burial, Huirou tradition, Yanqing tradition, and Minyun tradition modes.

3.3.3. Fitting Analysis of Different Tillage Mode

The near-surface PM2.5 and PM10 release concentrations of different conservation tillage modes under different wind speeds were analyzed, and the Origin18 software was used to achieve nonlinear curve fitting between wind speed and PM2.5 and PM10 release concentrations, and to establish straw mixing under different wind speeds. Fitting models of burial, stubble + straw mulching, straw mulching conservation tillage models, and near-surface PM2.5 and PM10 release concentrations. The results showed that the PM2.5 and PM10 release concentrations increased with the increase in wind speed in the modes of straw burial, straw mulching, and stubble + straw mulching, and the relational expressions were as follows (4):
Q = A + B L n ( V )
where Q is the release concentration of PM2.5 and PM10, V is the wind tunnel wind speed, and A and B are statistical parameters.
Under the traditional farming mode, the release concentrations of PM2.5 and PM10 increase exponentially with the increase in wind speed, and the relationship expression is as follows (5):
Q = A e B V
where Q is the release concentration of PM2.5 and PM10, V is the wind tunnel wind speed, and A and B are statistical parameters.
As shown in Table 6, from the correct equation, the release concentrations of PM2.5 and PM10 in the modes of straw burial, straw mulching, and stubble + straw mulching increase significantly with the increase of wind speed, and the adjusted R2 value is 0.86~0.97, which has an excellent fitting degree. Under the traditional tillage mode, the release concentrations of PM2.5 and PM10 increased exponentially with the increase in wind speed, and the adjusted R2 value was 0.82~0.99, which had an excellent fitting degree.
When the surface wind speed increases, the number of particles blown on the farmland surface increases, and straw is used as a cover on the surface of conservation tillage, which increases the coverage of non-erodible particles. Therefore, the step behavior of small particles on the surface is reduced within a specific wind speed range, thus inhibiting the release concentration of PM2.5 and PM10 on the surface. The fitting results show that under a wind speed of 1~8 m/s, the protective tillage mode with straw covering the surface has an apparent inhibitory effect on the release concentration of PM2.5 and PM10 in farmland compared with traditional tillage. Due to the limitations of wind tunnel test equipment, it is impossible to explore the inhibitory law of protective tillage on farmland dust under higher wind speeds.
From the overall change law, with the increase in wind power, the more significant the impact of surface coverage on the release concentration of PM2.5 and PM10 in farmland, the less surface coverage, and the greater the probability of inducing farmland soil dust. The variation trend of PM2.5 and PM10 release concentration with wind speed shows that with the continuous increase in wind speed, the release concentration of PM2.5 and PM10 increases gradually, but it is not a gradual process and has corresponding slow and steep variation intervals. When the wind speed interval of the wind tunnel is 4~8 m/s, the release amount of PM2.5 and PM10 on the surface increases to a large extent. In the higher wind speed range, the greater the degree of surface straw coverage, the better the inhibition effect on the release of PM2.5 and PM10 in farmland.

4. Discussion

The research on the wind erosion amount of farmland dust from bottom to top shows the wind erosion amount of straw burial, stubble + straw mulching, and straw mulching mode. The corresponding traditional farming mode is mainly concentrated in the sand collector with a height of 10 cm and 25 cm, indicating that the airflow in the farmland is challenging to transport the windblown sand dust of large particles on the surface to the atmospheric level. The research on the particle size of farmland dust shows that conservation tillage can reduce the large particle size of 90~250 μm by 31.6~74.7%. The inhibition effect is stubble + straw mulching > straw mulching > straw burial, which is consistent with Zang and wang et al.’s research on no-tillage mulching and harrow mulching to increase surface roughness and reduce the number of hefty particles blown near the surface [28,29].
Han evaluated the impact of bare soil wind-eroded dust on air particles and found that the contribution of PM10 dust to urban areas was about 41.45 μg/m3 [30]; Wu showed that farmland soil wind-eroded dust has a specific impact on PM10 concentrations in the near-surface air [31]. The monitoring group’s research on farmland near-surface PM2.5 and PM10 found that the conservation tillage model reduced farmland surface PM2.5 and PM10 by 17.2~42.5% compared with traditional farming by 25.6~40.8%. The mode of stubble + straw mulching has the best inhibitory effect on PM2.5 and PM10 near the surface. The reason may be that the straw stubble can fix the soil, protect the wind-erodible particles in the soil, and reduce the PM2.5 and PM10 released into the soil. Zhao has shown that the soil PM2.5 and PM10 emission intensity in spring and winter is wasteland > river beach > cultivated land. Planting in the wasteland for vegetation coverage can effectively reduce dust [32].
The wind tunnel test verification shows that with the increase in wind power, the greater the influence of the surface coverage on the release concentration of PM2.5 and PM10 in farmland. The less the surface coverage, the greater the probability of inducing farmland soil dust. The high-quality protective mode of stubble + straw mulch has the most apparent inhibition on the release concentration of PM2.5 and PM10 near the farmland surface, consistent with the research results on PM2.5 and PM10 near the surface. Zhou proved that the wind erosion amount of conservation tillage farmland and grassland was significantly less than traditional tillage farmland and sandy land [33]. Cong found that the marginal wind erosion effect of the test point was that the straw cover was more significant than the stubble height, and the interaction between stubble height and straw cover significantly affected the change in wind erosion amount [19].
In this study, the dust emission of conservation tillage and traditional tillage farmland is compared between the following two dimensions: the amount of windblown sand dust and the release of PM2.5 and PM10 near the surface of farmland. The mobile wind tunnel is used to simulate and verify the release of PM2.5 and PM10 near the farmland surface, and the release law of farmland dust under different wind speeds is explored. The test results show that the conservation tillage technology with stubble + straw mulching as the core can significantly inhibit farmland dust and significantly reduce the wind erosion of farmland dust and the concentration of near-surface PM2.5 and PM10. In addition, due to the variability of environmental factors, farmland dust monitoring needs to be carried out for a long time to further analyze the mechanism of conservation tillage on farmland dust suppression.

5. Conclusions

  • The monitoring results of farmland dust and wind erosion show that the amount of farmland wind erosion is mainly concentrated at a height of 0~25 cm, and the particle size of sand and dust is mainly concentrated in the range of 20~90 μm. The amount of farmland wind erosion of straw burial, stubble + straw mulching, and straw mulching is reduced by 29.37%, 40.73%, and 36.61%, respectively, compared with large particles of traditional farming, of which stubble + straw mulching has a more apparent inhibitory effect on farmland dust. The beneficial effects of farmland dust suppression are the following: stubble + straw mulching > straw mulching > straw burial;
  • The monitoring results of farmland PM2.5 and PM10 show that the near-surface PM2.5 and PM10 of straw mixed burying, stubble + straw mulching, and straw mulching are 42.5% and 40.8% lower than those of traditionally cultivated farmland, which is significantly higher than those of Yanqing straw mulching and Miyun straw mixed burying mode. The multiple linear regression analysis of the monitoring data shows that the near-surface PM2.5 and PM10 release concentration of farmland has the highest correlation with wind speed, followed by soil humidity and temperature;
  • The wind tunnel test verification shows that when the surface wind speed is in the range of 1~8 m/s, the release concentration inhibition trend of straw burial, stubble + straw mulching, and straw mulching modes PM2.5 and PM10 tends to be consistent with the monitoring results of farmland near-surface PM2.5 and PM10. In the wind tunnel test data, it is found that the released concentrations of PM2.5 and PM10 increase with the increase in wind speed under the modes of straw mixed burial, straw mulching, and stubble + straw mulching.

Author Contributions

Methodology, G.C., Q.W., H.L., S.G., D.X. and X.C.; Software, G.C., C.L. and X.C. Formal analysis, J.H. and C.L.; Investigation X.C.; Resources, S.G., D.X. and X.C.; Data curation, G.C., Q.W., H.L., J.H., C.L., S.G., D.X. and X.C.; Writing—original draft, G.C.; Writing—review and editing, Q.W., H.L., C.L. and X.C. Supervision, J.H.; Project administration, J.H. and S.G.; Funding acquisition, Q.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research is supported by the National Key R&D Program Research on the Mechanism of Conservation Tillage on Soil Texture and Crop Growth, grant number: 2016YFD070030102, and the horizontal project of Beijing Municipal Bureau of Agriculture and Rural Affairs “Conservation Farming Dust Monitoring Point Construction and Wind Erosion Prevention Effect Monitoring” grant number: 202005510710322 Co-funded.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Tian, M.; Gao, J.; Zhang, L.; Zhang, H.; Feng, C.; Jia, X. Effects of dust emissions from wind erosion of soil on ambient air quality. Atmos. Pollut. Res. 2021, 12, 101108. [Google Scholar] [CrossRef]
  2. Zheng, M.; Song, J.; Ru, J.; Zhou, Z.; Zhong, M.; Jiang, L.; Hui, D.; Wan, S. Effects of Grazing, Wind Erosion, and Dust Deposition on Plant Community Composition and Structure in a Temperate Steppe. Ecosystems 2021, 24, 403–420. [Google Scholar] [CrossRef]
  3. An, C.; Wang, R.; Zhou, H.; Li, Q.; Zhang, X.; Chang, C.; Guo, Z.; Li, J. Effect of No-Tillage in Autumn on Farmland Wind Erosion and Soil Properties in Bashang District. J. Desert Res. 2022, 42, 95–103. [Google Scholar]
  4. Zhang, H.; Gao, Y.; Sun, D.; Liu, L.; Cui, Y.; Zhu, W. Wind Erosion Changes in a Semi-Arid Sandy Area, Inner Mongolia, China. Sustainability 2019, 11, 188. [Google Scholar] [CrossRef] [Green Version]
  5. Wang, B.; Zhao, X.; Wang, X.; Zhang, Z.; Yi, L.; Hu, S. Spatial and temporal variability of soil erosion in the black soil region of Northeast China from 2000 to 2015. Environ. Monit. Assess. 2020, 192, 370. [Google Scholar] [CrossRef]
  6. Wu, Y.; Lin, S.; Tian, H.; Zhang, K.; Wang, Y.; Sun, B.; Liu, X.; Liu, K.; Xue, Y.; Hao, J.; et al. A quantitative assessment of atmospheric emissions and spatial distribution of trace elements from natural sources in China. Environ. Pollut. 2020, 259, 113918. [Google Scholar] [CrossRef]
  7. Fu, B.; Liu, Y.; Lü, Y.; He, C.; Zeng, Y.; Wu, B. Assessing the soil erosion control service of ecosystems change in the Loess Plateau of China. Ecol. Complex. 2011, 8, 284–293. [Google Scholar] [CrossRef]
  8. Guo, B.; Zang, W.; Yang, X.; Huang, X.; Zhang, R.; Wu, H.; Yang, L.; Wang, Z.; Sun, G.; Zhang, Y. Improved evaluation method of the soil wind erosion intensity based on the cloud–AHP model under the stress of global climate change. Sci. Total Environ. 2020, 746, 141271. [Google Scholar] [CrossRef]
  9. Qiu, Y.; Li, Y.; Yu, X.; Jia, G.; Sun, L.; Wang, Y. Effects of Straw Mulch on Soil Wind Erosion and Fine Particulate Matter Release in Farmland. J. Soil Water Conserv. 2020, 34, 131–136. [Google Scholar] [CrossRef]
  10. Lin, X.; Niu, J.; Yu, X.; Berndtsson, R.; Wu, S.; Xie, S. Maize residue effects on PM2.5, PM10, and dust emission from agricultural land. Soil Tillage Res. 2021, 205, 104738. [Google Scholar] [CrossRef]
  11. Pan, J.; Yan, P.; Sun, F.; Li, Y.; Liu, B.; Wang, Z.; Dong, R. Application of Ensemble Forecast and Linear Regression Method in Improving PM2.5 Forecast over Beijing Area. Environ. Monit. China 2019, 35, 43–52. [Google Scholar] [CrossRef]
  12. Karami, S.; Hamzeh, N.H.; Abadi, A.R.S.; Madhavan, B.L. Investigation of a severe frontal dust storm over the Persian Gulf in February 2020 by CAMS model. Arab. J. Geosci. 2021, 14, 2041. [Google Scholar] [CrossRef]
  13. Sun, L. Experimental Study on Protective Tillage Measures for Wind Erosion Prevention and Control of Farmland Soils in Beijing. Master’s Thesis, Beijing Forestry University, Beijing, China, 2019. Available online: https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD202001&filename=1019194871.nh (accessed on 16 February 2022).
  14. Csavina, J.; Field, J.; Félix, O.; Corral-Avitia, A.Y.; Sáez, A.E.; Betterton, E.A. Effect of wind speed and relative humidity on atmospheric dust concentrations in semi-arid climates. Sci. Total Environ. 2014, 487, 82–90. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Aimar, S.B.; Mendez, M.J.; Funk, R.; Buschiazzo, D.E. Soil properties related to potential particulate matter emissions (PM10) of sandy soils. Aeolian Res. 2012, 3, 437–443. [Google Scholar] [CrossRef]
  16. Zhao, P.; Tuo, D.; Li, H.; Duan, Y.; Kang, X.; Gong, Q.; Zhang, J. Effects of Soil Moisture and Physical Sand Content on Wind Erosion Modulus in Wind Tunnel Testing. Trans. Chin. Soc. Agric. Eng. 2012, 28, 188–195. [Google Scholar]
  17. Zhu, L.; Huang, X.; Shi, H.; Cai, X.; Song, Y. Transport pathways and potential sources of PM10 in Beijing. Atmos. Environ. 2011, 45, 594–604. [Google Scholar] [CrossRef]
  18. Liu, Y.; Wang, J.; Li, Z. Research Procession the Effects of Straw Mulchon Soil Moisture and Soil Erosion. Res. Soil Water Conserv. 2021, 28, 429–436. [Google Scholar] [CrossRef]
  19. Cong, P.; Yin, G.; Gu, J.; Li, W.; Huang, P. Effects of Stubble and Mulching on Soil Wind Erosion. Chin. J. Ecol. 2014, 33, 2060–2064. [Google Scholar] [CrossRef]
  20. Wasson, R.J.; Nanninga, P.M. Estimating wind transport of sand on vegetated surfaces. Earth Surf. Processes Landforms 1986, 11, 505–514. [Google Scholar] [CrossRef]
  21. Bressolier, C.; Thomas, Y.F. Studies on Wind and Plant Interactions on French Atlantic Coastal Dunes. J. Sediment. Petrol. 1977, 47, 331–338. [Google Scholar]
  22. Zang, Y.; Gao, H. Structural Design and Performance Test of Dust Sampler for Wind Erosion Measurements. Trans. Chin. Soc. Agric. Eng. 2006, 22, 46–50. [Google Scholar]
  23. Joshi, J.R. Quantifying the impact of cropland wind erosion on air quality: A high-resolution modeling case study of an Arizona dust storm. Atmos. Environ. 2021, 263, 118658. [Google Scholar] [CrossRef]
  24. Vos, H.C.; Fister, W.; Eckardt, F.D.; Palmer, A.R.; Kuhn, N.J. Physical Crust Formation on Sandy Soils and Their Potential to Reduce Dust Emissions from Croplands. Land 2020, 9, 503. [Google Scholar] [CrossRef]
  25. Wang, Q.; Wang, W.; Gong, S.; Li, W.; Jia, M.; Jia, Z.; He, J.; Mao, N.; Wang, S. An Automatic Monitoring Device for Farmland Dust. Beijing CN113418817A 2021. [Google Scholar]
  26. Pi, H.; Webb, N.P.; Huggins, D.R.; Sharratt, B. Critical standing crop residue amounts for wind erosion control in the inland Pacific Northwest, USA. CATENA 2020, 195, 104742. [Google Scholar] [CrossRef]
  27. Wu, S.; Niu, J.; Lin, X. Effects of Conservation Tillage Measures on Soil Wind Erosion in Yanqing, The Suburb of Beijing. Sci. Soil Water Conserv. 2020, 18, 57–67. [Google Scholar]
  28. Zang, Y.; Gao, H.; Zhou, J. Experimental Study on Soil Erosion by Wind under Conservation tillage. Trans. Chin. Soc. Agric. Eng. 2003, 2, 56–60. [Google Scholar]
  29. Wang, J. The Change Features and Influence Mechanism Research on Dynamic Roughness of Summer Monsoon Transition Zone. Master’s Thesis, Lanzhou University, Lanzhou, China, 2018. Available online: https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD201802&filename=1018979613.nh (accessed on 19 February 2022).
  30. Han, M. Effect of Open Source Blowing Dust Resulting from Wind Erosion of Bare Soil on Urban Ambient Air Particulate Matter. Environ. Pollut. Prev. 2010, 32, 5–8. [Google Scholar] [CrossRef]
  31. Wu, Y.; Wu, J.; Wang, L. Changes in the PM10 Concentrations of Air Near the Ground of Farmlands in Spring. J. Agro-Environ. Sci. 2020, 39, 1792–1802. [Google Scholar]
  32. Zhao, F.; Li, S.; Sun, H.; Li, N.; Li, G. Characteristics and Control Technology of Soil Dust in Different Land Types. Environ. Sci. Technol. 2019, 42, 38–43. [Google Scholar] [CrossRef]
  33. Zhou, J. Experimental Study on Soil Wind Erosion and Using Conservation Tillage to Reduce Wind Storm Disaster. Ph.D. Thesis, China Agricultural University, Beijing, China, 2004. Available online: https://kns.cnki.net/kcms/detail/detail.aspx?FileName=2004077690.nh&DbName=CDFD2004 (accessed on 26 February 2022).
Figure 1. Location and mode diagram of test site.
Figure 1. Location and mode diagram of test site.
Agriculture 12 00703 g001
Figure 2. Schematic diagram of sand dust collector.
Figure 2. Schematic diagram of sand dust collector.
Agriculture 12 00703 g002
Figure 3. Schematic diagram of wind erosion collection.
Figure 3. Schematic diagram of wind erosion collection.
Agriculture 12 00703 g003
Figure 4. Structure diagram of farmland dust online monitoring system.
Figure 4. Structure diagram of farmland dust online monitoring system.
Agriculture 12 00703 g004
Figure 5. Farmland dust online monitoring system.
Figure 5. Farmland dust online monitoring system.
Agriculture 12 00703 g005
Figure 6. Structural diagram of wind tunnel.
Figure 6. Structural diagram of wind tunnel.
Agriculture 12 00703 g006
Figure 7. Surface of test section.
Figure 7. Surface of test section.
Agriculture 12 00703 g007
Figure 8. Installation of dust measuring instrument.
Figure 8. Installation of dust measuring instrument.
Agriculture 12 00703 g008
Figure 9. Miyun straw burial.
Figure 9. Miyun straw burial.
Agriculture 12 00703 g009
Figure 10. Huairou stubble + straw mulching.
Figure 10. Huairou stubble + straw mulching.
Agriculture 12 00703 g010
Figure 11. Yanqing straw mulching.
Figure 11. Yanqing straw mulching.
Agriculture 12 00703 g011
Figure 12. Miyun traditional tillage.
Figure 12. Miyun traditional tillage.
Agriculture 12 00703 g012
Figure 13. Huairou traditional tillage.
Figure 13. Huairou traditional tillage.
Agriculture 12 00703 g013
Figure 14. Yanqing traditional tillage.
Figure 14. Yanqing traditional tillage.
Agriculture 12 00703 g014
Figure 15. Miyun straw burial.
Figure 15. Miyun straw burial.
Agriculture 12 00703 g015
Figure 16. Miyun traditional tillage.
Figure 16. Miyun traditional tillage.
Agriculture 12 00703 g016
Figure 17. Huairou stubble + straw mulching.
Figure 17. Huairou stubble + straw mulching.
Agriculture 12 00703 g017
Figure 18. Huairou traditional tillage.
Figure 18. Huairou traditional tillage.
Agriculture 12 00703 g018
Figure 19. Yanqing straw mulching.
Figure 19. Yanqing straw mulching.
Agriculture 12 00703 g019
Figure 20. Yanqing traditional tillage.
Figure 20. Yanqing traditional tillage.
Agriculture 12 00703 g020
Figure 21. Changes of PM2.5 concentrations at 10 cm height under different wind speeds.
Figure 21. Changes of PM2.5 concentrations at 10 cm height under different wind speeds.
Agriculture 12 00703 g021
Figure 22. Changes of PM10 concentrations at 10 cm height under different wind speeds.
Figure 22. Changes of PM10 concentrations at 10 cm height under different wind speeds.
Agriculture 12 00703 g022
Figure 23. Changes of PM2.5 concentrations at 20 cm height under different wind speeds.
Figure 23. Changes of PM2.5 concentrations at 20 cm height under different wind speeds.
Agriculture 12 00703 g023
Figure 24. Changes of PM10 concentrations at 20 cm height under different wind speeds.
Figure 24. Changes of PM10 concentrations at 20 cm height under different wind speeds.
Agriculture 12 00703 g024
Figure 25. PM2.5 concentration changes with wind speed at 10 cm height in the wind tunnel.
Figure 25. PM2.5 concentration changes with wind speed at 10 cm height in the wind tunnel.
Agriculture 12 00703 g025
Figure 26. PM10 concentration changes with wind speed at 10 cm height in the wind tunnel.
Figure 26. PM10 concentration changes with wind speed at 10 cm height in the wind tunnel.
Agriculture 12 00703 g026
Figure 27. PM2.5 concentration changes with wind speed at 20 cm height in the wind tunnel.
Figure 27. PM2.5 concentration changes with wind speed at 20 cm height in the wind tunnel.
Agriculture 12 00703 g027
Figure 28. PM10 concentration changes with wind speed at 20 cm height in the wind tunnel.
Figure 28. PM10 concentration changes with wind speed at 20 cm height in the wind tunnel.
Agriculture 12 00703 g028
Table 1. Wind erosion at each height (g/cm2).
Table 1. Wind erosion at each height (g/cm2).
Monitoring PointTreatment MethodSampling TimeHeight (g/cm2)Total Wind Erosion
10 cm25 cm60 cm100 cm150 cm
MiyunStraw burial10.00910.00540.00280.00280.00200.0801
20.01150.00730.00280.00360.0028
30.01230.00840.00420.00330.0018
Traditional tillage10.01230.00750.00420.00330.00270.1134
20.01510.01060.00560.00640.0037
30.01720.01030.00780.00500.0017
HuairouStubble
+ straw
mulching
10.00780.00650.00300.00280.00130.0582
20.00750.00450.00260.00210.0012
30.00880.00540.00210.00300.0009
Traditional tillage10.01450.01240.00360.00330.00150.0982
20.01360.01170.00250.00260.0012
30.01330.01210.00210.00280.0010
YanqingStraw mulching10.01480.00830.00470.00280.00060.0826
20.01270.00760.00430.00220.0003
30.01030.00690.00400.00100.0021
Traditional tillage10.01710.01110.00770.00810.00110.1303
20.02070.01330.00460.00370.0037
30.01590.01160.00470.00310.0039
Note: the sampling time is from October to December 2020; Miyun: 13 November 2020, 28 November 2020, 13 December 2020; Huairou: 9 November 2020, 24 November 2020, 9 December 2020; Yanqing: 7 November 2020, 22 November 2020, 7 December 2020.
Table 2. Comparison of wind erosion monitoring results at monitoring points.
Table 2. Comparison of wind erosion monitoring results at monitoring points.
Monitoring PointsMonitoring DaysTotal Wind Erosion (g/cm2)
Conservation TillageTraditional TillageDecrease (%)
Miyun450.08010.113429.37
Huairou450.05820.098240.73
Yanqing450.08260.130336.61
Table 3. Linear regression analysis of variance of PM2.5 and PM10 release concentration.
Table 3. Linear regression analysis of variance of PM2.5 and PM10 release concentration.
Variation
Source
Sum of SquaresdfMean SquareFp
PM2.5Regression8.23942.059710.76<0.001 ***
Temperature2.053912.053910.730.002 ***
Humidity2.170812.170811.350.001 **
Wind speed2.151212.151211.240.002 ***
Rainfall0.153910.15390.80.374
Error9.3756490.1913
Total17.614553
PM10Regression8.316842.079211.1<0.001 ***
Temperature2.007812.007810.720.002 ***
Humidity2.788912.788914.880 ***
Wind speed2.18112.18111.640.001 ***
Rainfall0.146110.14610.780.382
Error9.1812490.1874
Total17.49853
Note: *** is extremely significant (p < 0.01) ** significant (0.01 < p < 0.05).
Table 4. Two factor variance analysis of PM2.5 and PM10 release under different tillage mode and wind speed.
Table 4. Two factor variance analysis of PM2.5 and PM10 release under different tillage mode and wind speed.
Variation SourceSum of SquaresdfMean SquareFp
PM2.5Tillage mode19,830.553966.113.80<0.001 ***
Wind speed67,052.3416,763.158.31<0.001 ***
Tillage mode * Wind speed7673.320383.71.3350.232
Error8624.530287.5
Total334,441.060
PM10Tillage mode141,395.9294875.712.73<0.001 ***
Wind speed32,496.156499.216.97<0.001 ***
Tillage mode * Wind speed12,912.020645.61.690.095
Error114,920.030383.1
Total502,80060
Note: *** is extremely significant (p < 0.01) * more significant (0.05 < p < 0.1).
Table 5. Multiple comparison of different farming methods (Duncan method).
Table 5. Multiple comparison of different farming methods (Duncan method).
FactornSubset
Mean ValueSignificance
PM2.5Stubble + straw mulching1034.2c
Straw mulching1049.4bc
Straw burial1060.2b
Huairou tradition1060.8b
Yanqing tradition1077.5a
Minyun tradition1090.4a
PM10Stubble + straw mulching1041.4c
Straw mulching1058.6bc
Straw burial1072.1b
Huairou tradition1075.2b
Yanqing tradition10105.3a
Minyun tradition10105.6a
Note: the same superscript in the same column indicates that the difference is not significant (p > 0.05), and different letters indicate that the difference is significant (p < 0.05).
Table 6. Fitting equation of farmland PM2.5 and PM10 release under different surface wind speeds.
Table 6. Fitting equation of farmland PM2.5 and PM10 release under different surface wind speeds.
Processing ModeFit EquationStatistical ParametersProcessing ModeFit EquationStatistical Parameters
ABR2adjABR2adj
Straw mulching
10 cm (PM2.5)
Q = A + B L n ( V ) 12.06 ± 7.3222.98 ± 4.640.947Yanqing tradition Q = A e B V 27.70 ± 6.810.18 ± 0.040.895
Straw mulching
20 cm (PM2.5)
4.24 ± 15.0145.05 ± 9.520.926Yanqing
tradition
36.38 ± 5.150.20 ± 0.0210.971
Straw mulching
10 cm (PM10)
7.60 ± 12.0435.22 ± 7.640.924Yanqing tradition35.65 ± 7.650.19 ± 0.030.934
Straw mulching
20 cm (PM10)
18.68 ± 18.6840.21 ± 11.850.862Yanqing tradition49.10 ± 8.910.19 ± 0.030.952
Straw burial
10 cm (PM2.5)
Q = A + B L n ( V ) 15.65 ± 7.3930.48 ± 4.690.972Minyun
tradition
Q = A e B V 33.18 ± 10.360.18 ± 0.050.853
Straw burial
20 cm (PM2.5)
19.65 ± 15.8042.75 ± 10.030.919Minyun
tradition
44.76 ± 9.530.18 ± 0.030.922
Straw burial
10 cm (PM10)
23.97 ± 9.0131.95 ± 5.720.966Minyun
tradition
42.41 ± 12.430.16 ± 0.040.822
Straw burial
20 cm (PM10)
35.36 ± 18.9144.13 ± 12.000.914Minyun
tradition
57.93 ± 12.820.16 ± 0.030.892
Stubble + straw
mulching
10 cm (PM2.5)
Q = A + B L n ( V ) −0.74 ± 5.8225.37 ± 3.690.960Huairou
tradition
Q = A e B V 20.50 ± 4.620.205 ± 0.0330.938
Stubble + straw
mulching
20 cm (PM2.5)
4.58 ± 7.9227.01 ± 5.020.942Huairou
tradition
27.17 ± 5.250.20 ± 0.030.946
Stubble + straw
mulching
10 cm (PM10)
2.85 ± 8.0527.83 ± 5.110.941Huairou
tradition
27.05 ± 5.360.19 ± 0.030.943
Stubble + straw
mulching
20 cm (PM10)
6.42 ± 11.6632.15 ± 7.400.908Huairou
tradition
27.89 ± 3.170.23 ± 0.020.987
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Chen, G.; Wang, Q.; Li, H.; He, J.; Lu, C.; Gong, S.; Xu, D.; Cao, X. Research on the Effect of Conservation Tillage Mode on the Suppression of Near-Surface Dust in Farmland. Agriculture 2022, 12, 703. https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050703

AMA Style

Chen G, Wang Q, Li H, He J, Lu C, Gong S, Xu D, Cao X. Research on the Effect of Conservation Tillage Mode on the Suppression of Near-Surface Dust in Farmland. Agriculture. 2022; 12(5):703. https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050703

Chicago/Turabian Style

Chen, Guibin, Qingjie Wang, Hongwen Li, Jin He, Caiyun Lu, Shaojun Gong, Dijuan Xu, and Xinpeng Cao. 2022. "Research on the Effect of Conservation Tillage Mode on the Suppression of Near-Surface Dust in Farmland" Agriculture 12, no. 5: 703. https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050703

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop